Intraurban Analysis of Surface Urban Heat Island From Disagregated Thermal Radiance Images

Surface Urban Heat Islands (SUHI) are areas with higher surface temperatures than their surroundings. Several studies have used thermal images from satellites to research the influence of urbanization on surface temperature patterns, however the low spatial resolution of thermal sensors limits the analysis of LST intraurban variations. Attempting to overcome this limitation, we used the Enhanced Physical Model (EPM) for disaggregation of land surface temperature (DLST) to generate fine scale LST for Sao Paulo city in Brazil. This method uses a linear regression and Planck’s law to combine NDVI, NDWI and UI to estimate LST at finer spatial detail. First, we calibrate the method by upscaling an ASTER thermal band to 1000 m and using EPM to estimate the original 100 m thermal band. The original and estimated ASTER thermal bands achieved and R² of 0.66. Following, we apply the EPM model to estimate the LST at 15 m and compare it with data from meteorological stations. The 15 m LST image facilitated the identification of potential SUHIs. The EPM model provides an enhanced product with higher level of spatial detail, which allows researchers to identify changes of surface temperature that would not be evident from an ASTER LST (90 m spatial resolution) product. In summary, the model allowed us to quantify and map the influence of different urbanization patterns on the LST distribution.Ilhas de calor de superfície (ICS)são áreas com temperature de superfície maior do que as áreas ao redor. Vários estudos tem usado imagens termais de satélite para investigar a influência da urbanização nos padrões de temperatura de superfície; entretanto a baixa resolução espacial dos atuais sensores termais limita a análise dos padrões de variação intraurbana de temperatura de superfície. Com o objetivo de surpassar essa limitação, nós utilizamos o the Enhanced Physical Model (EPM) para gerar dados de temperatura de superfície com maior nível de detalhamento para a cidade de São Paulo- Brasil. Esse método utiliza um modelo de regressão linear e a lei de Planck para combinar NDVI, NDWI e UI para estimar a temperatura de superfície com maior nível de detalhes espaciais.  Primeiro, para calibrar o modelo, nós reamostramos uma banda termal ASTER para 1000 m e utilizamos o método EPM para estimar a banda original de 100 m. A banda termal estimatada de 100 m atingiu um R2= 0.66 em relação a banda termal original. A seguir,  nós aplicamos o método EPM para estimar a temperatura de superfície à 15 m. A imagem de temperatura de superfície de 15 m facilitou a identificação de potenciais ilhas de calor de superfície. O modelo EPM fornece um produto com alto grau de detalhamento espacial, o que permite que pesquisadores identifiquem as mudanças de temperatura de superfície que não seriam evidentes na imagem  termal ASTER original (90 m de resolução espacial). Em suma, o modelo nos permitiu quantificar e mapear a influência de diferentes padrões de urbanização na distribuição dos padrões de temperatura de superfície

MELHORIA DO PROCESSO DE CORREÇÃO GEOMÉTRICA DE IMAGENS CBERS-CCD PELO USO DE AMOSTRAS GEORREFERENCIADAS CLASSIFICADAS

As imagens da série de satélites CBERS são distribuídas gratuitamente, mas para que seja possível utilizá-las, é necessário aplicar um método de correção geométrica. É proposta uma melhoria do processo de correção automática de forma a selecionar as melhores amostras de referência a partir das quais é possível definir pontos de controle usados para o cálculo dos parâmetros do modelo usado na correção. Para demonstrar a eficácia, o método proposto é aplicado em um conjunto de imagens CBERS usando as amostras de imagens selecionadas

MAPEAMENTO DA COBERTURA VEGETAL EM ESCALA REGIONAL DO ESTADO DE MINAS GERAIS UTILIZANDO IMAGENS MODIS

O objetivo desse trabalho foi avaliar o potencial das imagens MODIS para mapeamento da cobertura vegetal no estado de Minas Gerais. O uso de imagens de satélite de resolução espacial moderada e resolução temporal alta, quase diária, é uma opção viável para o monitoramento da vegetação e de sua dinâmica, seja ela natural ou cultivada. O Estado de Minas Gerais, devido à sua variedade de biomas e fitofisionomias foi selecionada como área de estudo. A bordo das plataformas Terra e Aqua, o sensor MODIS adquire dados com 250 m de resolução espacial, que foram utilizados como base para a formação de uma série temporal para o ano de 2004. A acurácia da classificação foi estimada baseada nos pontos amostrais coletados em campo e na comparação com o mapa de vegetação desenvolvido pelo IEF/UFLA. O mapa oriundo das imagens MODIS apresentou Índice Kappa de 0,73 quando comparado com o conjunto de pontos de campo, e 0,84 quando comparado com o mapa de referência (IEF/UFLA). Os resultados obtidos permitem concluir que os dados do sensor MODIS podem ser utilizados para o mapeamento e monitoramento efetivo das classes de cobertura vegetal em escala regional. Palavras Chave: Mapeamento. Vegetação. MODIS. Minas Gerais. Vegetation cover mapping of Minas Gerais State in regional scale using MODIS images The objective of this work was to evaluate the potential of MODIS images for mapping vegetation cover in Minas Gerais State, Brazil. The use of moderate resolution satellite with high temporal resolution, almost daily, is a viable option to monitor the natural or cultivated vegetation and its dynamics. Minas Gerais State in Brazil, due to its diverse biomes and phytofisionomies was selected as study area. Onboard the Terra and Aqua platforms, the MODIS sensor acquire images with 250m spatial resolution, that were used to form the 2004 time series dataset. The classification accuracy was estimated based on sample points collected in the field and by comparing with the vegetation map developed by IEF/UFLA. The map originated from MODIS data yield a Kappa Index of 0.73 when compared with sample points dataset and 0.84 when compared with the reference map (IEF/UFLA). The results obtained allow to concluding that MODIS sensor data can be used for effective mapping and monitoring of vegetation cover classes in regional scale. Key words: Mapping. Vegetation. MODIS. Minas Gerais

AVALIAÇÃO DE IMAGENS SIMULADAS DA CÂMERA MUX DO SATÉLITE CBERS-4 APLICADAS À ANÁLISE AMBIENTAL

Métodos de simulação de imagens orbitais são frequentemente utilizadas naavaliação do desempenho de determinado sistema-sensor. A partir do empregodestas técnicas é possível analisar e estimar o comportamento das imagens que serãogeradas pelos sensores projetados, possibilitando uma estimativa da qualidade e dasaplicações decorrentes do lançamento do satélite. Neste contexto, torna-se defundamental importância a análise das imagens orbitais e das possíveis aplicaçõesprovenientes do satélite CBERS-4, que deve ser lançado ao final do ano de 2014 eterá uma política de distribuição gratuita dos dados. Deste modo, o objetivo destetrabalho é avaliar o potencial da câmera MUX do CBERS-4, com 20 m de resoluçãoespacial, para mapeamento de cobertura do solo do município de Apuí no estado do Amazonas. Para isto, as imagens MUX são simuladas a partir de imagens do satéliteRapidEye e filtragem baseada no modelo do processo de imageamento. Para avaliaros resultados da simulação, uma imagem da câmera TM do satélite Landsat-5 éprocessada para produzir um mapa de cobertura de solo, que é comparada ao mapagerado pela imagem MUX simulada do CBERS-4. Os valores de NDVI calculadosa partir das imagens MUX simulada e TM-5 também são analisados. Osexperimentos mostram que o processamento das imagens simuladas da câmeraMUX apresentaram resultados semelhantes aos das imagens do sensor TM. Emgeral, as classificações da cobertura do solo para os sensores MUX e TMapresentam boa concordância, com acurácia global de 87% e Kappa de 0,72. Ainda,percebe-se que os valores de NDVI estimados pela MUX são em média 25%maiores que os valores estimados pelo TM e apresentam uma correlação de 85%(significante a 0.05, teste t-student)

Pátio cercado por árvores de espinho e outras frutas, sem ordem e sem simetria: O quintal em vilas e arraiais de Minas Gerais (séculos XVIII e XIX)

This article analyses urban and rural backyards in Minas Gerais, in the late18th and early 19th centuries. Sources include probate records, foreign travelers accounts, administrative documents and iconography. These spaces are interpreted as a part of material culture, as provisioning grounds, and places of sociability and family intimacy. The connections of yards within households and the surrounding streetscapes are examined, revealing that they can be viewed as instruments of balance in the overall urban landscape.O texto objetiva analisar os quintais urbanos e rurais em Minas Gerais, ao final do século XVIII e início do século XIX. Interpreta evidências documentais de inventários post mortem, narrativas de viajantes estrangeiros, documentos administrativos e iconográficos, interpretando esses espaços, na perspectiva da cultura material, como lugares de abastecimento alimentar, sociabilidades e da intimidade familiar. Considera a ligação dos quintais com a casa e as ruas e os vê como espaços de equilibrio da paisagem urbana

The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe

Global, regional, and national progress towards Sustainable Development Goal 3.2 for neonatal and child health: all-cause and cause-specific mortality findings from the Global Burden of Disease Study 2019

Background Sustainable Development Goal 3.2 has targeted elimination of preventable child mortality, reduction of neonatal death to less than 12 per 1000 livebirths, and reduction of death of children younger than 5 years to less than 25 per 1000 livebirths, for each country by 2030. To understand current rates, recent trends, and potential trajectories of child mortality for the next decade, we present the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 findings for all-cause mortality and cause-specific mortality in children younger than 5 years of age, with multiple scenarios for child mortality in 2030 that include the consideration of potential effects of COVID-19, and a novel framework for quantifying optimal child survival. Methods We completed all-cause mortality and cause-specific mortality analyses from 204 countries and territories for detailed age groups separately, with aggregated mortality probabilities per 1000 livebirths computed for neonatal mortality rate (NMR) and under-5 mortality rate (USMR). Scenarios for 2030 represent different potential trajectories, notably including potential effects of the COVID-19 pandemic and the potential impact of improvements preferentially targeting neonatal survival. Optimal child survival metrics were developed by age, sex, and cause of death across all GBD location-years. The first metric is a global optimum and is based on the lowest observed mortality, and the second is a survival potential frontier that is based on stochastic frontier analysis of observed mortality and Healthcare Access and Quality Index. Findings Global U5MR decreased from 71.2 deaths per 1000 livebirths (95% uncertainty interval WI] 68.3-74-0) in 2000 to 37.1 (33.2-41.7) in 2019 while global NMR correspondingly declined more slowly from 28.0 deaths per 1000 live births (26.8-29-5) in 2000 to 17.9 (16.3-19-8) in 2019. In 2019,136 (67%) of 204 countries had a USMR at or below the SDG 3.2 threshold and 133 (65%) had an NMR at or below the SDG 3.2 threshold, and the reference scenario suggests that by 2030,154 (75%) of all countries could meet the U5MR targets, and 139 (68%) could meet the NMR targets. Deaths of children younger than 5 years totalled 9.65 million (95% UI 9.05-10.30) in 2000 and 5.05 million (4.27-6.02) in 2019, with the neonatal fraction of these deaths increasing from 39% (3.76 million 95% UI 3.53-4.021) in 2000 to 48% (2.42 million; 2.06-2.86) in 2019. NMR and U5MR were generally higher in males than in females, although there was no statistically significant difference at the global level. Neonatal disorders remained the leading cause of death in children younger than 5 years in 2019, followed by lower respiratory infections, diarrhoeal diseases, congenital birth defects, and malaria. The global optimum analysis suggests NMR could be reduced to as low as 0.80 (95% UI 0.71-0.86) deaths per 1000 livebirths and U5MR to 1.44 (95% UI 1-27-1.58) deaths per 1000 livebirths, and in 2019, there were as many as 1.87 million (95% UI 1-35-2.58; 37% 95% UI 32-43]) of 5.05 million more deaths of children younger than 5 years than the survival potential frontier. Interpretation Global child mortality declined by almost half between 2000 and 2019, but progress remains slower in neonates and 65 (32%) of 204 countries, mostly in sub-Saharan Africa and south Asia, are not on track to meet either SDG 3.2 target by 2030. Focused improvements in perinatal and newborn care, continued and expanded delivery of essential interventions such as vaccination and infection prevention, an enhanced focus on equity, continued focus on poverty reduction and education, and investment in strengthening health systems across the development spectrum have the potential to substantially improve USMR. Given the widespread effects of COVID-19, considerable effort will be required to maintain and accelerate progress. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd

Activities in Remote Sensing

A brief description of some recent activities in Remote Sensing at INPE is presented. The description does not intend to be complete; it is limited to the remote sensing activities that have been contributing in the solution of the problems that affect the remote sensing area. Topics include: research and development on GIS, image processing , remote sensing applications such as deforestation in Amazonia as well as some information about CBERS program